1563 search results for "regression"

Passing-Bablok Regression: R code for SAS users

September 2, 2013
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Passing-Bablok Regression: R code for SAS users

While at the Joint Statistical Meeting a few weeks ago I was talking to a friend about various aspects to clinical trials. He indicated that no current R package was able to perfectly reproduce Passing-Bablok (PB) regression so that it exactly matched SAS. He ultimately wrote a couple of functions and kindly shared them with

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Nonparametric (local polynomial) regression in R

August 26, 2013
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Local polynomial regression models can be used as a more flexible alternative to linear regression. However, the nonparametric regression models are slightly more difficult to estimate and interpret than linear regression. This video explains almost ev...

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Estimation, prediction, and evaluation of logistic regression models

August 26, 2013
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I provide an introduction to using logistic regression for prediction (binary classification) using the Titanic data competition from www.Kaggle.com as an example. I use models to predict in missing data, estimate a logistic regression model on a trai...

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R vs Python: Practical Data Analysis (Nonlinear Regression)

August 26, 2013
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R vs Python: Practical Data Analysis (Nonlinear Regression)

I’ve written a few previous posts comparing R to Python in terms of symbolic math, optimization, and bootstrapping. All of these posts were pretty popular. The last one especially. Many of the commenters brought up the fact that R, while … Continue reading →

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Non-linear regression in R

August 25, 2013
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Non-linear regression in R

Here is the link to the article: http://rpubs.com/hughes/7812 There you will discover how to simulate and fit: power function, Michaelis-Menten equation and sigmoid curves in R, the fit is done by least-square using the ‘nls’ function.Filed under: R and Stat Tagged: NLS, R

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Exporting Results of Linear Regression with Robust Standard Errors

August 24, 2013
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Residuals from a logistic regression

August 23, 2013
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Residuals from a logistic regression

I always claim that graphs are important in econometrics and statistics ! Of course, it is usually not that simple. Let me come back to a recent experience. A got an email from Sami yesterday, sending me a graph of residuals, and asking me what could be done with a graph of residuals, obtained from a logistic regression ?...

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Forecasting From Log-Linear Regressions

August 22, 2013
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Forecasting From Log-Linear Regressions

I was in (yet another) session with my analyst, "Jane", the other day, and quite unintentionally the conversation turned, once again, to the subject of "semi-log" regression equations.After my previous rant to discussion with her about this matter, I've tried to stay on the straight and narrow. It's better for my blood pressure, apart from anything else! Anyway, somehow...

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Endogenous Spatial Lags for the Linear Regression Model

August 18, 2013
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Endogenous Spatial Lags for the Linear Regression Model

Over the past number of years, I have noted that spatial econometric methods have been gaining popularity. This is a welcome trend in my opinion, as the spatial structure of data is something that should be explicitly included in the empirical modelling procedure. Omitting spatial effects assumes that the location co-ordinates for observations are unrelated

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Enhanced meboot package, simulating regression standard errors

August 11, 2013
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In my June 25 post I described R- (i) code to change scale without changing the mean, and (ii) code to make a probability distribution symmetric by modifying order statistics.  Both are commonly encountered problems by R programmers.  My coauthor Javier Lopez-de-Lacalle of Spain has incorporated an efficient version of my code inside the maximum entropy bootstrap (meboot) package in R See the package...

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